Any implications of this diagonal element inequality?

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    Element Inequality
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Discussion Overview

The discussion revolves around the implications of a diagonal element inequality between two positive definite matrices A and B. Participants explore the consequences of this inequality on the eigenvalues of the matrices, considering both theoretical and mathematical perspectives.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Exploratory

Main Points Raised

  • One participant notes that if A and B are positive definite matrices with diagonal elements satisfying A_{ii} ≥ B_{ii}, this relationship holds under any unitary change of coordinates and questions the implications for eigenvalue inequalities.
  • Another participant suggests that the matrix A-B is positive semidefinite (p.s.d) and assumes the matrices are real, leading to the conclusion that the diagonal elements of U^T(A-B)U are non-negative for any orthogonal matrix U.
  • A different participant proposes that the eigenvalues of A dominate those of B, stating that for the i^{th} largest eigenvalues, the sum of the first k eigenvalues of A is greater than or equal to that of B, referencing a result from Horn and Johnson regarding hermitian matrices.
  • A later reply expresses appreciation for the insights provided, indicating that the discussion has been helpful.

Areas of Agreement / Disagreement

Participants present multiple viewpoints regarding the implications of the diagonal element inequality on eigenvalues, with no consensus reached on the strongest conclusions or interpretations of the results.

Contextual Notes

Participants assume the matrices are real and positive definite, but the discussion does not clarify the implications of these assumptions on the broader context of the results.

winterfors
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Given two definite positive definite matrices A and B of identical size with the following relationship of their diagonal elements:

[tex]A_{ii} \geq B_{ii}[/tex] (no summation)

which also holds after any unitary change of coordinates

[tex]\textbf{A}'=\textbf{U}^T\textbf{A}\textbf{U}[/tex]

where [tex]\textbf{U}[/tex] complete set of orthonormal vectors.


Question: What does this imply in terms of inequalities on the eigenvalues of the matrices?

The sum of eigenvalues of A is of course equal of greater than the sum of eigenvalues B:s eigenvalues, but this is true even without allowing for change of coordinates. I'm sure you must be able to deduce something stronger when the inequality holds under any unitary coordinate change...
 
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My linear algebra is very rusty so be careful of the argument below.

A-B is p.s.d .

I am assuming the matrices are real.

Now from the given condition we have for any orthogonal matrix U, the diagonal elements of [itex]U^T (A-B) U[/itex] are non negative.

In particular choose [itex]U[/itex] to be the orthogonal matrix corresponding to the spectral decomposition of [itex]A-B[/itex] and we get all its eigenvalues as non negative.
 
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I think this also implies that the eigenvalues of A dominate the eigenvalues of B in the following way: if [itex]\lambda_i(A)[/itex] is the [itex]i^{th}[/itex] largest eigenvalue of A and [itex]\lambda_i(B)[/itex] is similarly defined. Then [itex]\sum_{i=1}^{k} \lambda_i(A) \geq \sum_{i=1}^{k} \lambda_i(B)[/itex] for [itex]k=1,\dots,n[/itex].

This follows from the fact that for two hermitian matrices A and B of the same order we have (4.3.27 Horn and Johnson)
[itex]\sum_{i=1}^{k} \lambda_i(A+B) \geq \sum_{i=1}^{k} \lambda_i(A) + \sum_{i=1}^{k} \lambda_i(B)[/itex], in particular substituting the pair [itex]A-B,B[/itex] and noting [itex]\lambda_i(A-B) \geq 0[/itex] we get the result.
 
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This was exactly what I was looking for, many thanks!
 

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